Sentiment Analysis of Social Network Content

2015 ◽  
Author(s):  
Shambhavi Dinakar ◽  
Pankaj Andhale ◽  
Manjeet Rege
Keyword(s):  
Social Network ◽  
Sentiment Analysis

scholarly journals Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yanni Liu ◽  
Dongsheng Liu ◽  
Yuwei Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Smart City ◽  
Topic Model ◽  
Rapid Development ◽  
Mobile Internet ◽  
Time Curve ◽  
Public Opinions ◽  
The Social

With the rapid development of mobile Internet, the social network has become an important platform for users to receive, release, and disseminate information. In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. In view of social networks’ characteristics such as short text, rich topics, diverse sentiments, and timeliness, this paper conducts text modeling with words co-occurrence based on the topic model. Besides, the sentiment computing and the time factor are incorporated to construct the dynamic topic-sentiment mixture model (TSTS). Then, four hot events were randomly selected from the microblog as datasets to evaluate the TSTS model in terms of topic feature extraction, sentiment analysis, and time change. The results show that the TSTS model is better than the traditional models in topic extraction and sentiment analysis. Meanwhile, by fitting the time curve of hot events, the change rules of comments in the social network is obtained.

Social Network Sentiment Analysis and Message Clustering

2019 ◽  
pp. 18-31 ◽  
Author(s):  
Alexander A. Kharlamov ◽  
Andrey V. Orekhov ◽  
Svetlana S. Bodrunova ◽  
Nikolay S. Lyudkevich
Keyword(s):  
Social Network ◽  
Sentiment Analysis

scholarly journals Study of Automotive Brands Popularity in Indonesia Using Twitter Data

2016 ◽  
Vol 3 (1) ◽  
pp. 23-33
Author(s):  
Stevent Efendi ◽  
Alva Erwin ◽  
Kho I Eng
Keyword(s):  
Social Media ◽  
Social Network ◽  
Sentiment Analysis ◽  
Automotive Industry ◽  
Real World ◽  
The Internet ◽  
Brand Preference ◽  
Twitter Data ◽  
Wide Range ◽  
Widespread Phenomenon

Social media has been a widespread phenomenon in the recent years. People shared a lot of thought in social media, and these data posted on the internet could be used for study and researches. As one of the fastest growing social network, Twitter is a particularly popular social media to be studied because it allows researchers to access their data. This research will look the correlation between Twitter chatter of a brand and the sales of brands in Indonesia. Factors such as sentiment and tweet rate are expected to be able to predict the popularity of a brand. Being one of the biggest industries in Indonesia, automotive industry is an interesting subject to study. A wide range of people buys vehicles, and even gather as communities based on their car or motorcycle brand preference. The Twitter results of sentiment analysis and tweet rate will be compared with real world sales results published by GAIKINDO and AISI.

Sentiment Analysis of Social Media as Tool to Improve Customer Retention

2017 ◽  
pp. 635-648
Author(s):  
Wafaa A. Al-Rabayah ◽  
Ahmad Al-Zyoud
Keyword(s):  
Social Media ◽  
Social Network ◽  
Literature Review ◽  
Competitive Advantage ◽  
Sentiment Analysis ◽  
Customer Retention ◽  
Unstructured Data ◽  
Amount Of Information ◽  
Business Applications ◽  
The Web

Sentiment analysis is a process of determining the polarity (i.e. positive, negative or neutral) of a given text. The extremely increased amount of information available on the web, especially social media, create a challenge to be retrieved and analyzed on time, timely analyzed of unstructured data provide businesses a competitive advantage by better understanding their customers' needs and preferences. This literature review will cover a number of studies about sentiment analysis and finds the connection between sentiment analysis of social network content and customers retention; we will focus on sentiment analysis and discuss concepts related to this field, most important relevant studies and its results, its methods of applications, where it can be applied and its business applications, finally, we will discuss how can sentiment analysis improve the customer retention based on retrieved data.

Sentiment Analysis of Social Media as Tool to Improve Customer Retention

2017 ◽  
pp. 207-223
Author(s):  
Wafaa A. Al-Rabayah ◽  
Ahmad Al-Zyoud
Keyword(s):  
Social Media ◽  
Social Network ◽  
Literature Review ◽  
Competitive Advantage ◽  
Sentiment Analysis ◽  
Customer Retention ◽  
Unstructured Data ◽  
Amount Of Information ◽  
Business Applications ◽  
The Web

Sentiment analysis is a process of determining the polarity (i.e. positive, negative or neutral) of a given text. The extremely increased amount of information available on the web, especially social media, create a challenge to be retrieved and analyzed on time, timely analyzed of unstructured data provide businesses a competitive advantage by better understanding their customers' needs and preferences. This literature review will cover a number of studies about sentiment analysis and finds the connection between sentiment analysis of social network content and customers retention; we will focus on sentiment analysis and discuss concepts related to this field, most important relevant studies and its results, its methods of applications, where it can be applied and its business applications, finally, we will discuss how can sentiment analysis improve the customer retention based on retrieved data.

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